User device group formation

ABSTRACT

Systems and methods for the forming of user device groups are presented. In one example, a message including location information indicating a geographic location of a first user device is received from the first user device. Values representing logical connection strengths between the first user device and other user devices are calculated using the location information. A first device group is determined for the first user device based on the calculating of the values representing the logical connection strengths, the first device group including a plurality of the other user devices.

CROSS-REFERENCE TO RELATED PATENT DOCUMENTS

This patent application claims the benefit of priority of U.S.Provisional Application No. 61/466,849, entitled “SHARING CONTENT AMONGMULTIPLE DEVICES,” filed Mar. 23, 2011, which is hereby incorporatedherein by reference in its entirety.

COPYRIGHT NOTICE

A portion of the disclosure of this patent document contains materialthat is subject to copyright protection. The copyright owner has noobjection to the facsimile reproduction by anyone of the patent documentor the patent disclosure as it appears in the Patent and TrademarkOffice patent files or records, but otherwise reserves all copyrightrights whatsoever. The following notice applies to the software and dataas described below and in the drawings that form a part of thisdocument: Copyright 2012, Color Labs, Inc. All Rights Reserved.

TECHNICAL FIELD

This application relates generally to user devices and, morespecifically, to systems and methods for forming user device groups.

BACKGROUND

As portable communication devices, such as cellular phones, tabletcomputers, and laptop computers, continue to evolve to provide improvedaudio, video, and still image capture capability, the opportunity forusers of these devices to capture various forms of content and sharethat content with others, such as friends and relatives, continues toincrease. In some situations, a user may distribute the content toothers by way of explicitly determining the recipients of the content,manually attaching the content to an e-mail, “picture mail,” or similarcommunication message, and transmitting the message and attached contentusing the communication device of the user to the communication devicesof each of the recipients. Typically, the user distributing the contenthas programmed the contact information, such as an e-mail address ortelephone number, of each of the recipients into his communicationdevice prior to capturing the content to be distributed.

In another example, the user distributing the content may post thecontent to a separate Internet website or other data site accessible bythe intended recipients of the content, and subsequently inform therecipients of the message as to how to access the content. Typically,the site providing access to the content is password-protected orprovides some other means by which only the intended recipients mayaccess the content.

BRIEF DESCRIPTION OF THE DRAWINGS

Some embodiments are illustrated by way of example and not limitation inthe figures of the accompanying drawings in which:

FIG. 1 is a block diagram illustrating an example communication system;

FIG. 2 is a flow diagram illustrating an example method of sharingcontent in the communication system of FIG. 1;

FIG. 3 is a block diagram illustrating modules of an example clientdevice of an example communication system;

FIG. 4 is a block diagram illustrating modules of an example server ofan example communication system;

FIG. 5 is a diagram of an example data structure identified with a groupof client devices of a communication system;

FIG. 6 is a flow diagram illustrating an example method of joining aclient device to a group of client devices within a communicationsystem;

FIG. 7 is a flow diagram illustrating an example method of determining agroup for a client device to join in a communication system;

FIG. 8 is a flow diagram illustrating an example method of sharingcontent among a group of client devices in a communication system;

FIGS. 9A through 9L are a set of screen shots of an example userinterface provided by a client device in a communication system; and

FIG. 10 is a diagrammatic representation of a machine in the exampleform of a computer system within which a set of instructions for causingthe machine to perform any one or more of the methodologies discussedherein may be executed.

DETAILED DESCRIPTION

Example methods and systems for the forming of user device groups, suchas device groups formed primarily for the sharing of content, including,for example, photographs, audio content, video content, and textualcontent, are discussed. In the following description, for purposes ofexplanation, numerous specific details are set forth in order to providea thorough understanding of example embodiments. It will be evident,however, to one skilled in the art that the present subject matter maybe practiced without these specific details. It will also be evidentthat the types of software development described herein are not limitedto the examples provided and may include other scenarios notspecifically discussed.

In accordance with an example embodiment, FIG. 1 illustrates acommunication system 100 including multiple client (user) devices 102A,102B, 102C, 102D (more generally, devices 102) coupled with a server 104via a communication network 106. In this specific example, three of theclient devices 102A, 102B, 102C belong to a group 110 for which theserver 104 distributes content 120 captured by one of the group clientdevices 102A, 102B, 102C to the remaining members of the group 110. Inthis implementation, a fourth client device 102D does not belong to thegroup 110, and thus does not receive the content 120 posted to the group110 by any of the group client devices 102A, 102B, 102C. While FIG. 1displays a group 110 of three member client devices 102A, 102B, 102C,any number of client devices 102 greater than one may constitute a group110. As is described in greater detail below, the member client devices102 of the group 110 may be determined by way of interactions betweenthe client devices 102, such as communications between the devices 102,the physical proximity of the devices 102, and other parametersdescribing how closely or strongly the client devices 102 may belogically connected or related to each other during a period of time.

FIG. 2 is a simplified flow diagram of an example method 200 of sharingcontent 120 among client devices 102, as shown in FIG. 1. However, othercommunication systems utilizing different components or systems mayemploy the method depicted in FIG. 2 in other examples. In the method200, the server 104 determines the client devices 102 belonging to thegroup 110 (operation 202), as mentioned above. One of the client devices102A of the group 110 may then capture the content 120 (operation 204),such as audio, video, still image, or the like. The client device 102Athen transfers the content 120 to the server 104 (operation 206), whichtransfers the content 120 to the other member client devices 102B, 102Cof the group 110 (operation 208). In one example, the content 120 mayalso be distributed to a separate communication node 108 (shown inFIG. 1) via an Application Programming Interface (API) of the node 108so that the content 120 may be accessed from other devices as well.Examples of the communication node 108 may be a server hosting aparticular website or messaging service, such as Shutterfly® orTwitter®.

In another example, the method 200 may be encoded as instructions on anon-transitory computer-readable storage medium, such as, for example,an integrated circuit, magnetic disk, or optical disk, which arereadable and executable by one or more computers or other processingsystems, such as the client devices 102 and the server 104 of FIG. 1.

In FIG. 1, the client devices 102 are capable of capturing content 120,such as photographs, audio and/or video, textual data (such as thatgenerated by a user of the device), or any other type of content 120 ofinterest to one or more users, and displaying that content 120 to theuser of the device 102. Examples of the client devices 102 may include,but are not limited to, mobile communication devices, such as cellularphones, personal digital assistants (PDAs), digital cameras, laptopcomputers, tablet computers, and netbooks.

The communication network 106 may be any communication network capableof facilitating communications, including the transfer of the content120, either by wire or wirelessly, between the client devices 102 andthe server 104. Examples of the communication network 106 may include,but are not limited to, any and/or all of a wide-area network (such asthe Internet), a local-area network (LAN) (such as an IEEE 802.11x(Wi-Fi) network), a Bluetooth connection, a Near Field Communication(NFC) connection, an Ethernet connection, a mobile or cellularcommunications device network (such as a third generation (3G) or fourthgeneration (4G) connection), and a microcell network. The communicationnetwork 106 may constitute a direct connection between the server 104and each of the client devices 102, or may include any number oftransmitters, receivers, switches, repeaters, and other components tofacilitate communications between the server 104 and the client devices102.

The server 104 may be any device or system capable of receiving thecontent 120 from the client devices 102, forwarding the content 120 toother client devices 102, and performing other tasks associated with theserver 104 as further described below. The server 104 may be, forexample, a processor-based system programmed to coordinate the formingof a group 110 of client devices 102 and facilitating the transfer ofthe content 120 generated by one or more member devices 102 of the group110 to other members of the group 110. In one example, the server 104may implemented as one or more components, such as a processing systemand associated database, possibly embodied as a “cloud” solutionaccessible via the communication network 106. In another example, theserver 104 may be a system or device deployed at a communication serviceprovider site, a conference center, or a location at which a particularevent or meeting is taking place. In some implementations, the server104 may be combined with one or more components of the communicationnetwork 106, or devices attached thereto, such as a wireless ormicrocell access point, a localized hub, or even one of the clientdevices 102. For example, instead of using an explicit client-servertopology, the communication system 100 may be configured as apeer-to-peer network, with one or more of the client devices 102performing the duties of the server 104 as described herein.

In some embodiments, the client device group 110 represents a number ofclient devices 102 that are identified by way of “interactions” detectedby the server 104 that occur between the member devices 102.Interactions between client devices 102 may be both passive (forexample, client devices 102 left in close proximity to each other forperiods of time) and active (for example, a call, SMS message, or othercommunication initiated from one client device 102 to another). Types ofinteractions between client devices 102 that may cause them to beidentified with the same group 110 may include, but are not limited to,the number of communications that have occurred between the clientdevices 110, the length of time of the communications between the clientdevices 102, the physical distance between the client devices 102, alength of time during which the client devices 102 are in close physicalproximity, and other circumstances and/or activities involving theclient devices 102. In some implementations, two client devices 102 ofthe same group 110 need not maintain close proximity or engage in directcommunications between the devices 102 if some type of logicalinteraction of a unique or important character between the two devices102 is occurring, or has occurred. For examples, client devices 102whose users have identified each other as “friends,” and thus may havecommunicated directly and extensively in the past, may belong to a group110 regardless of the physical proximity of the associated clientdevices 102. Such friends may include, but are not limited to, personalfriends, friends of friends, relatives, and users sharing or holding oneor more common interests or backgrounds. Such logical interactions,together with the more explicit interactions between users mentionedabove, may be considered interactions or logical relationships betweenthe various users or user devices for the purpose of defining the clientdevice group 110 in some examples.

Any or all of these interactions, as detected by, or communicated to,the server 104 may contribute to the server 104 determining orcalculating a “connection strength” or “affinity” between two of theclient devices 102. In some examples, client devices 102 exhibiting arelatively higher connection strength or affinity tend to indicate thatthe devices 102 should be identified with, or be members of, a group110, while a relatively lower connection strength or affinity betweenclient devices 102 tends to indicate that the devices 102 should not bemembers of the same group 110. In at least some embodiments, since theserver 104 may detect or receive information regarding interactionsbetween client devices 102, as described above, the focus of theinformation describing the interactions may be on the client devices 102themselves, and not on the users of the client devices 102. As a result,the server 104 need not collect personally identifiable information ofany users of the client devices 102 in order to determine or calculatethe connection strength or affinity between any two client devices 102.Personally identifiable information would normally include sensitiveinformation such as full name, driver's license number, credit cardaccount numbers, and the like.

Additionally, since the server 104 may join client devices 102 into agroup on the basis of client device 102 interactions, explicit guidancefrom users regarding which client devices 102 to include in a network orgroup 110 may be unnecessary. Further, the server 104 may construct thegroup 110 and manage membership of client devices 102 in the group 110without any formalized client device 102 authentication process, such asthe explicit use of passwords or other security measures.

In some examples, the connection strength or affinity between two ormore client devices 102 may not remain constant over time. For example,two users capturing photographs with their respective client devices ata particular event may never communicate directly with each other, andmay not be present at any other location at the same time for anysignificant length of time. As a result, the server 104 may treat such aconnection between the two client devices 102 as temporary or“ephemeral,” thus causing the two client devices 102 to be associatedwith the same group 110 for a brief time period. Thus, membership in agroup 110 may wax and wane over time, and even the group 110 may beshort-lived. Thus, such a group 110 may be considered a kind of “elasticnetwork” or “dynamic network” in which membership may change over timedue to continuing interactions (or lack thereof) between client devices102 within the group 110, as well as external to the group 110. In thiscase, the term “network” is employed to refer to the group 110 of clientdevices 102, as described above.

In one embodiment, once the server 104 forms a group 110 of clientdevices 102, any member of the group 110 may post content 120, such asaudio, video, text, still images, and the like, to the server 104, whichmay then distribute the content 120 to the other members of the group110. In the specific example of FIG. 1, the server 104 has formed thegroup 110 including a first client device 102A, a second client device102B, and a third client device 102C. A fourth client device 102D is notincluded in the group 102D due to not possessing a connection strengthor affinity comparable to the connection strength or affinity betweenthe other client devices 102A, 102B, 102C. When the first client device102A then posts content 120 to the server 104 via the communicationnetwork 106, the server 104, in turn, forwards the content 120 to allother members of the group 110 (in this case, the second client device102B and the third client device 102C), but not to those client devices102 that are not members of the group 110 (in this example, the fourthclient device 102D). Similarly, the server 104 may distribute contentposted by the second client device 102B or the third client device 102Cto the other members of the group 110.

FIGS. 3 and 4 are block diagrams of example embodiments of a clientdevice 300 and associated server 400, respectively, which may serve asone of the client devices 102 and the server 104 depicted in FIG. 1. InFIG. 3, the client device 300 includes a number of software and orhardware modules, such as a user interface module 302, a locationservices module 304, an environment detection module 306, a timesynchronization module 308, a coasting module 310, a content cachingmodule 312, a content push mechanism module 314, a content ingestionmodule 316, and a tuning parameters module 318. In other client devices300, one or more of the modules 302-318 may be omitted, and one or moremodules not depicted in FIG. 3 may be included.

In the client device 300, the user interface module 302 may facilitateaccess of the user of the client device 300 to various aspects of thesharing of content 120 within a group 110, including, but not limitedto, providing explicit input as to which group 110 to join, postingcontent 120 to the group 110, and receiving content 120 posted by otherclient devices 102 in the group 110. More specific examples of the userinterface provided by the user interface module 302 are discussed ingreater detail below in conjunction with FIGS. 9A through 9L.

The location services module 304 may provide or generate informationregarding the physical location of the user client device 300. In oneexample, the location service module 304 may determine location by wayof signals received from the GPS system, an Assisted GPS (A-GPS) system,a Wi-Fi Positioning System, and/or cell-site triangulation. The locationservices module 304 may receive such signals by way of circuitry of theclient device 300 and process one or more of the signals to determinethe location.

The environment detection module 306 may receive signals from one ormore sensors residing on, or in communication with, the client device300 to indicate various environmental conditions in the vicinity of theclient device 300. Such signals may indicate, for example, atmosphericpressure, temperature, light, velocity, acceleration, orientation, andso on, as generated by sensors such as light meters, accelerometers,gyroscopes, thermometers, and the like. For example, persistent changesin acceleration may indicate the client device is located in a movingcar, or the detection of multiple voices may indicate presence within acrowd. The environment detection module 306 may also employ signals fromvarious communication network interfaces, such as Near-FieldCommunication (NFC) signals, Bluetooth® communication signals, Wi-Ficommunication signals, and the like to supplement and enhance thelocation information of the client device 300 generated by the locationservices module 306 to more closely define the location of the clientdevice 300.

The time synchronization module 308 may provide timing information, suchas a timestamp, that is periodically received from the server 400 (andmaintained locally in the time synchronization module 308) to mark whenvarious location data (from the location services module 304) and/orenvironmental data (from by the environment detection module 306) werereceived or generated. As is described more fully below, the locationand environmental data, along with their timing information, may beuploaded to the server 400, which may then compare that data withcorresponding data from other client devices 300 to determine therelative physical proximity of the client devices 300, and thus at leastpartially determine which of the client devices 300 may be groupedtogether.

Generally, the coasting module 310 aids in determining how long theclient device 300 may remain in a particular group 110 during periods oftime in which the client device 300 has lost contact with the server400, or during periods of intermittent contact with the server 400. Inone example, the coasting module 310 takes into account various types ofinformation, such as location information, time information, andactivity of the client device 300 within the group 110 (for example,posting of content 120 to the group 110, initiation of the group 110 bythe client device 300, and so on), to help determine if the clientdevice 300 should remain in same group 110 as it did prior to the lastsignificant contact with the server 400.

The content caching module 312 may store locally on the client device300 content 120 that has been captured at the client device 300 but hasnot been posted to the server 400, such as during times when the clientdevice 300 has lost contact with the server 400. In response to theconnection between the server 400 and the client device 300 beingrestored, the cached content, including photos, audio, video,annotations, and the like, may then be uploaded to the server 400 forsubsequent transfer to the other client devices 400 of the group 110.

The content push mechanism module 314 facilitates reception of content120 and other data from the server 400 via the communication network 106under a “push” data transfer model. For example, a Comet web applicationmodel may be employed to receive content 120 and other data under a“hanging GET” protocol, in which the server 400 maintains a HyperTextTransfer Protocol (HTTP) request from the client device 300 indefinitelyto push the content 120 and other data to the client device 400.

The content ingestion module 316 may be responsible for taking thecontent 120 captured at the client device 300 and possibly modifying,adjusting, or otherwise processing the content 120 before posting thedata to the server 400. For still image content 120, examples of suchprocessing may include, but are not limited to, scaling the image, andadjusting the resolution, orientation, brightness, sharpness, color,contrast, or focus of the image. These operations may depend on severalfactors, including, but not limited to, the capture and displaycapabilities of the client device 300, and the speed of thecommunication network 106 coupling the client device 300 and the server400. The content ingestion module 316 may also package various metadatawith the content 120, such as the location and environmental datadiscussed above, possibly to allow the server 400 to determine the group110 to which the content 120 is to be distributed.

The tuning parameters module 318 may receive one or more parameters fromthe server 400 that may condition or modify the operation of one or moreof the modules 302-316 of the client device 300. In one implementation,the tuning parameters module 318 may receive parameters that affect theoperation of the coasting module 310 based on the last known location ofthe client device 300. For example, the length of time the client device104 may be out of contact with the server 104, or the distance theclient device 300 has traveled, before being removed from a group 110may be adjusted based on available network access in the area of theclient device 300. In some examples, other tuning parameters may bereceived from the server 400 that affect other modules, such as thelocation services module 304, the environment detection module 306, andthe content push module 314. Such parameters may include, for example,how to process the proximity and environmental data being received atthe client device 300, what communication address the client device 300should use to receive content 120 updates, and so on.

In FIG. 4, the server 400 may include, for example, any or all of an APImodule 402, a user metadata module 404, an interaction recording module406, an affinity calculator module 408, a group content ranker module410 (which, in turn, may include a group candidate indexer 412 and acandidate scorer module 414), a push/subscribe module 416, a presencemodule 418, a content queue module 420, a face detection/recognitionmodule 422, and an image quality detection module 424. In other servers400, one or more of the modules 402-424 may be omitted, and othermodules not depicted in FIG. 4 may be added.

The user metadata module 404 contains information associated with eachof multiple client devices 300 for various users, such as identifiersassociated with the client device 300 to allow communication with theother client devices 300. The user metadata may also include a list ofcontacts (such as other client devices 300) with which the client device300 has interacted in the past. In one example, the contacts may bedivided into an active contact list and an all contacts list. Based onrecent interactions between the client device 300 and other clientdevices 300, the server 400 may promote client devices 300 from the allcontacts list to the active list for the client device 300, and demoteclient devices 300 in the active list to the all contacts list. Thepromotion and demotion operations are the result of calculations made bythe affinity calculator module 408, described below. The contacts listscan also be modified due to direct override instructions from the userof the client device 300. Other user preferences, such as which groups110 the client device 300 has initiated or formed, and which groups 110the client device 300 are to remain in regardless of previous clientdevice 300 interactions (referred to below as “pinning,”) may be storedvia the user metadata module 404 as well. In some implementations,additional contacts may be added to the lists based on one or moreinferences or algorithms. For example, a particular prospective contactmay be added to the contact lists of a client device 300A based on, forexample, triangle closing, in which the client device 300A and theprospective contact each have one or more common contacts.

The API module 402 facilitates at least two functions via two othermodules of the server 400. For one, the API module 402 enables therecording of interactions between client devices 300 via the interactionrecording module 406. Further, the API module 402 facilitates theanswering of queries regarding affinity with other client devices 300,which are calculated by the affinity calculator module 408. In oneexample, the API module 402 maintains an affinity score between eachclient device 300 and other client devices based on the recordedinteractions, with the affinity scores (generated by the affinitycalculator module 408) being compared with a threshold value todetermine whether other client devices 300 are placed in the activecontacts list or the all contacts list maintained in the user metadatamodule 404, with a contact in the active contacts list indicating thatthe contact is active. The threshold may be a floating threshold in someimplementations, the value of which may depend on how many other clientdevices 300 with which the first client device 300 has interacted. Otherfactors may affect the value of the threshold in some examples.

In one example, the interaction recording module 406 may keep track ofthe most recent interactions between the client device 300 and anotherclient device 300, such as 100 or 200 interactions, in a type offirst-in, first-out (FIFO) scheme. As a result, older interactions aredeleted in most cases, as they are presumably of lesser importance thannewer interactions. Some interactions may not be treated strictlyaccording to such a FIFO scheme in some examples, such as another clientdevice 300 that the first client device 300 has either “friended” orexplicitly blocked, as such user preferences may be preserved,regardless of their age.

In the example of FIG. 4, the group content ranker module 410 includestwo sub-modules: a candidate indexer module 412 and a candidate scorermodule 414. Generally, the candidate indexer module 412 determines oneor more possible groups 110 into which the client device 300 belongs.Such action may occur, for example, when the client device 300 is firstpowered up, or when an application that implements the various methodsdiscussed herein is initiated. The candidate indexer module 412 may thenforward the one or more identified groups 110 to the candidate scorermodule 414, which may then generate a score, such as by way of aformula, each time the group content ranker module 410 is requested toperform the function. For example, the group content ranker module 410performs the ranking for a client device 300 relative to the one or moregroups 110 available when the client device 300 first attempts to join agroup 110, or when the client device uploads an item of content 120,such as a photograph, video clip, audio segment, text block, or thelike.

The group content ranker module 410 may then use the scores provided bythe candidate scorer module 414 to sort and rank the content 120according to the one or more groups 110. The group 110 with the highestscore relative to the content 120 may then be selected for the clientdevice 130 to join. In some implementations, the user of the clientdevice 300 may have specifically indicated a preference for a particulargroup 110, in which case the group content ranker module 414 may selectthat group 110 for the content 120. In one example, the group contentranker module 414 compares the highest score for a group 110 to athreshold value. If the score attains the threshold, the server 400 mayrecommend the associated group 110 to the client device 300 for joining,or automatically join the client device 300 to the group 110. If,instead, the score is less than the threshold, the server 400 maygenerate a new group 110 for the client device 300 and push metadataassociated with that group 110 to other client devices 300, such asthose located proximate to the first client device 300, and allow thoseclient devices 300 the option of joining the newly generated group 110.In one example, the group content ranker module 414 receives metadataregarding proximity, connections, and the like between the first clientdevice 300 and other client devices 300 each time the group contentranker module 414 ranks the candidate groups 110 for particular content120 to adjust the ranking.

The presence module 418 may be employed by the server 400 to determinewhich client devices 300 are located within some predetermined distanceof the first client device 300. This server 400 may use this informationto identify those client devices 300 that may be interested in joining anew group initiated by the first client device 300. To this end, thepresence module 418 may maintain a real-time index of those clientdevices 300 in proximity to the first client device 300. For thoseclient devices 300 not proximate to the first client device 300, theserver 400 may poll those client devices 300 to determine their locationin order to provide a group 110 with which they may be associated.

The push/subscribe module 416 may provide the functionality for theserver 400 to push content to the client devices 300 of a particulargroup 110, as well as to provide one or more potential groups 110 to aclient device 300, to which the user of the client device 300 may thensubscribe or join. In one example, the server 400 automatically joinsthe client device 300 to the group 110 without requesting confirmationfrom the client device 300. As mentioned above, the pushing of content120 may be facilitated by way of a Comet web application model todistribute content 120 and other data to the client devices 300 under a“hanging GET” protocol.

The content queue module 420 may maintain and manage content 120 that isyet to be distributed to one or more client devices 300. For example,the push/subscribe module 420 may not distribute each item of content120 immediately to all client devices 300 of a group 110 if the numberof client devices 300 is high enough to cause a significant delay indistributing the content 120 to all of the group 110 members. In suchcases, the push/subscribe module 416 may then forward the content 120(and possibly any associated metadata) to the content queue module 420,which then may hold the content 120, or transfer the content 120 to onlya subset of the group 110 member devices, until a later time. Thedecision to queue the content 120 in the content queue module 420 may bebased upon several factors, possibly including, but not limited to, thenumber of client devices 300 associated with the group 110 and theavailable bandwidth of the communication network 106.

The face detection/recognition module 422 may be employed to adjuststill or video image content (for example, by cropping) based on thefaces or other important features detected in the image prior todistributing the resulting content 120 to the group 110. In one example,the face detection/recognition module 422 may also correlate facialfeatures with names of people in order to generate metadata identifyingthe person represented in the content 120. The metadata may then beattached to the content 120 prior to distribution to the group 110.

The image quality detection module 424 may process still images, one orframes of a video segment, and the like to ascertain one or more aspectsof the images or frames, such as scaling, resolution, orientation,brightness, sharpness, color, contract, focus, and the like. The imagequality detection module 424 may then determine the relative quality ofthe image and decide whether the image or frame is to be distributed tothe remaining client devices 300 of the group, or should be discardedinstead. In some implementations, the image quality detection module mayadjust the image, such as cropping out-of-focus areas or lessinteresting portions of the image, brightening the image, and so forthbefore distributing the image to the group 110.

FIG. 5 provides a graphical representation of a group data structure 500that maintains data related to the content 120 associated with aparticular group 110. In this particular example, the group datastructure 500 provides a root 501 or “parent” structure to whichmultiple “leaf” or “child” data structures 502-510 may be associated.Examples of the child data structures 502-510 may include, but are notlimited to, a group identifier 502, a data structure 504A-504N for eachphotograph or still image associated with the group 110, a datastructure 506A-506N for each video segment associated with the group110, a data structure 508A-508N for each audio segment associated withthe group 110, and a data structure 510A-510N for each annotationassociated with the group 110. In some examples, an annotation may be atext string or other set of characters relating comments, likes, userratings, and so forth from users of client devices 300 of the group 110.The annotations may be associated with particular content 120 or withthe group 110 in general, such as invitations to other client devices120 to join a particular group. Any or all of the root 501 and the leafdata structures 502-510 may also include, or be linked with, metadatadiscussed above that is associated with the client device 300 postingthe content 120, possibly including, but not limited to, the identity ofthe posting client device 300, the time of capture of the content 120,information describing the location of the client device 300, and theenvironmental parameters sensed at the client device 300. As describedabove, this information may be used by the group content ranker module410 to rank the various possible groups 110 associated with the content120.

Each group data structure 500 may be logically associated with eachclient device 300 identified as a member of the group 110. Further, theserver 400 may organize the client devices 300 according to theirinvolvement in the group 110 as either contributing devices (forexample, those client devices 300 providing or posting content 120 tothe group 110) or presence devices (those client devices that arereceiving content 120 but not providing the content 120). In someimplementations, the presence devices are not considered to possess asstrong a connection to the groups as the contributing devices, as theymay possess only “ephemeral presence” in the group by being associatedwith the group temporarily before being associated with another group110, such as by physically moving away from the first group 110 withoutcontributing content 120, and then coming in close proximity to a secondgroup 110.

FIG. 6 provides portions of an overall block diagram of operations andinteractions between the server 400 and a client device 300A attemptingto join a group 110 according to one specific example of a method ofdistributing content within a group 110. Other client devices 300 otherthan the client device 300A are generally referred to as client devices300B, as shown in FIG. 8. Other possible examples may omit one or moreoperations and communications described in FIG. 6, or may add otheroperations and communications not shown therein.

In FIG. 6, a client device 300A may provide an initial message to theserver 400 via the API module 402 upon powering up or initiating aspecific application (operation 602). Such a message may be termed a“bootstrap” message. In response, the server 400 may supply one or moretuning parameters via the API module 402 for various modules of theclient device 300 (operation 604), as described above. At some pointafter receiving the tuning parameters, the client device 300A retrievesor generates location information (via the location service module 304)and environmental data (via the environment detection module 306)(operation 606). The client device 300A may then transmit a recurringmessage (sometimes referred as a polling or “I am here” message)containing the generated location and environment data to the server 400via the API module 402 (operation 608).

In response to the polling message 602, the API module 402 of the server400 may record information specific to the client device 300A (operation610). For example, the API module 402 may inform the presence module 418of this information so that the presence module 418 may determine otherpotential client devices 300B within physical proximity to the firstclient device 300A. The API module 402 may also cause the push/subscribemodule 416 to subscribe the client device 300A to the server 400 so thatthe client device 300A will receive updates regarding new content 120,new groups 110, new member client devices 300B for a group 110 to whichthe client device 300A belongs, and so on.

Also in response to the polling message 608, the API module 402 mayinvoke the group content ranker module 410 with the received locationand presence information to generate group recommendations for theclient device 300A (operation 612). A more detailed example of thisoperation is provided in FIG. 7. In that example, the group contentranker module 410 may provide the client device 300A location andenvironmental information to the candidate indexer module 412 (operation702) so that the candidate indexer module 412 may identify candidategroups 110 for the client device 300A (operation 704). The candidategroups 110 may include all groups 110 in the vicinity of the clientdevice 300A. In one example, the vicinity of the client device 300A maybe defined relative to a predefined area, so that the candidate indexermodule 412 may then determine the location of the client device 300Arelative to other client devices 300 for various groups 110 in the sameor adjacent areas. Other groups 110 not in the vicinity may also beconsidered, such as current or recent groups 110 to which “friends” ofthe client device 300A may belong (or have recently belonged), or towhich the client device 300A may have been attached previously.

The candidate indexer module 412 may then provide the candidate groupsto the candidate scorer 414 (operation 706), which may thenindependently score each of the candidate groups 110 provided by thecandidate indexer module 412 (as described above) (operation 708) andprovide those scores to the group content ranker module 410 (operation710). In one example, the candidate scorer module 414 may receiveseveral input factors to determine the score for a particular group. Onesuch type of factor is explicit actions taken by users of the clientdevice 300A regarding previous groups 110 or associated client devices300 to which the client device 300A was attached. Such actions include,for example, manually joining a previous group 110, manually creating aprevious group 110, manually maintaining an attachment to a previousgroup 110 regardless of subsequent changes in location (referred to as“pinning” to a group 110), and designating a particular client device300 as a “friend.” Information may also be provided to the candidateindex scorer module 414 whether such a friend is present in thecandidate group 110, and whether the friend contributed content 120 tothe candidate group 110 (including annotations). The candidate indexscorer module 414 may also consider actions of the user of the clientdevice 300A regarding previous interactions with the candidate group110, such as presence in the group 110 and contribution of content 120and/or annotations. In some examples, the candidate index scorer module414 may also consider one or more factors indicating the relative“loneliness” of the client device 300A based on the number of friends,contributors, and the like previously associated with the client device300A in other groups 110. The candidate index scorer module 414 may alsoconsider the time, location, and environmental information provided bythe client device 300A via the API module 402 of the server 402.

The candidate index scorer module 414 may represent any and/or all ofthese factors by numerical values, which the candidate index scorermodule 414 may then subsequently weight to determine the relativeimportance of each factor. Various maximum or minimum limits may beplaced on each of the values. Further, one or more various time-varyingfunctions may be applied to each weighted factor value, such as, forexample, exponential decay, asymptotic growth, or a decreasing ramp, torepresent the effect of the passage of time on the factor. For example,factors relating to the location of the client device 300A at varioustimes may be conditioned with an exponential decay function such thatolder locations become less important to the scoring over time. Anasymptotic growth function which approaches a particular maximum valuemay be applied to factors addressing the amount of contribution activityof friends of the client device 300A. Other factors, such as the manualactions of the user of the client device 300A relative to the joining,creating, and pinning of groups 110 may not be conditioned with aparticular time-varying function.

Each of the resulting values may then be combined by way of anaggregating function to determine the overall score for a candidategroup 110. In one example, the overall algorithm, including the factorweights, the applied time-varying functions, and the aggregatingfunction may remain constant or static, while in other implementations,they may be altered over time as a result of one or more machinelearning algorithms.

Upon receiving the candidate groups and their scores, the group contentranker module 410 either selects one of the candidate groups 110 for theclient device 300A, or generates a new group 110 for the client device300A (operation 712). In one example, the group content ranker module410 compares the score of each candidate group 110 to a predeterminedthreshold. If at least one of the candidate groups 110 possesses a scoremeeting or exceeding the threshold, the group content ranker module 410may select one or more of the candidate groups 110 with the highestscores exceeding the threshold for the client device 300A to join.Instead, if none of the candidate groups 110 possesses a score as highas the threshold, the group content ranker module 410 may create a newgroup 110 for the client device 300A to join. In the case of a new group110, group content ranker module 410 may also associate the location andenvironmental metadata for the client device 300A with the new group 110so that other client devices 300B in the vicinity of the client device300A may be asked to join the new group 110.

In some implementations, the group content ranker module 410 may alsotake into account previous user preferences regarding groups in order toselect a group 110 for the client device 300A. Such preferences mayinclude, for example, favoring the joining of a group 110 that includesspecific client devices 300B, such as “friends,” or blocking the joiningof a group 110 that includes other specific client devices 300B. Suchpreferences may override the scores for the candidate groups 110provided by the candidate scorer module 414.

After the group content ranker module 410 selects the one or more groups110 for the client device 300A to join potentially, the group contentranker module 410 may then associate the client device 300A to theselected group or groups 110 (operation 714) by indicating to thepresence module 418 that the client device 300A is to be joined to thecandidate group or groups 110, and is to be removed from other groups110 in which the client device 300A may have been active. Thepush/subscribe module 416 may also be employed to subscribe the clientdevice 300A to all real-time changes detected for that group (operation716), such as new content 120, changes in group 110 membership, and soon. The client device 300A may also be subscribed to other candidategroups 110 nearby in case a switch to one of those groups 110 issubsequently warranted due to location changes and other circumstances.

For at least some of the embodiments described herein, the algorithmsemployed to perform various functions regarding the formation of a group110 (such as those performed by the affinity calculator module 408, thecandidate indexer module 412, candidate scorer module 414, and/or thegroup content ranker module 410, for example) may be based on one ormore types of modeling. Examples of such modeling may include, but arenot limited to, logistic regression, Bayesian networks, random forestmodeling, and neural networks.

Returning to FIG. 6, the API module 402 of the server 400 provides therecommended groups to the client device 300 (operation 614). In oneexample, the API module 402 provides a strong recommendation for one ofthe recommended groups 110 for the client device 300A to join based onthe highest score generated by the candidate scorer module 414. Inresponse, the user of the client device 300A selects one of therecommended groups 110 (operation 616). The client device 300A may theninform the server 400 of the selection via the API module 402 (operation618). In another example, the server 400 may simply select thehighest-ranked group 110 for the client device 300A and inform theclient device 300A of the selection of the group 110, in which case theclient device 300A need not select a particular group 110 to join orinform the server 400 of the selection. In some cases, the client device300A may instead be able to explicitly change the group 110 selected bythe server 400 to another of the candidate groups 110.

In one implementation, the server 400 may be capable of detectingcircumstances in which multiple client devices 300 attempt to create anew group 110 nearly simultaneously, which should logically be the samegroup 110. In this example, the server 400 analyzes one or more factors,including, but not limited to, the location and environmental conditionsof the client devices 300 attempting to create a new group 110, and thetiming of the creation of the groups 110. Based on that analysis, theserver 400 may instead create a single group 110 for all of the involvedclient devices 300 to join.

At this point, the client device 300A and the server 400 are inagreement as to the particular group 110 that the client device 300A hasjoined. Further, the entire evaluation process of operations 606-618 ofdeciding whether the client device 300A should remain in the currentgroup 110 (or be removed from the group 110, possibly in order to join anew group 110) may be performed again in response to one or more events620. One such event 620 may be the expiration of a timeout timer, or“heartbeat” counter, which may cause the client device 300A to gatherlocation and environmental data (operation 606) and transmit anotherpolling message containing that data (operation 608) once a certainperiod of time (for example, three or five minutes) has elapsed sincethe last polling message was transmitted. The heartbeat counter may bemaintained either in the server 400 or the client 300A. Another suchevent 620 may be the generation of a new group 110 in the vicinity ofthe client device 300A, in which case the server 400 informs the clientdevice 300A of the new group 110, causing the client device 300A totransmit another polling message 608. Further, another event 620 mayoccur if the client device 300A detects significant physical movement(via location or environmental data of the client device 300A). In someimplementations, the user of the client device 300A may explicitlyrequest a re-initiation of the grouping process, thus constitutinganother type of the event 620. In each case, the server 400 may thendetermine that the client device 300A should either remain in thecurrent group 110, or switch to another group 110, based on the scoresgenerated for each group 110 in the server 400. In other examples, thegrouping operations 606-618 may also occur in response to the creationor capture of content 120 in the client device 300A, which is thenuploaded to the server 400 for distribution to other member clientdevices 300B of the group 110.

In some implementations, a group 110 may be strongly identified with, or“pinned” to, a particular location or venue, such as a local pub, or astadium or arena. As a result, the user of the client device 300A mayexplicitly request a re-initiation of the grouping process when enteringsuch an area, or the server 400 may initiate the process in response todetecting that the client device 300A has entered that area.Accordingly, the server 400 may thus provide the client device 300A withthe option of joining that particular group 110. Similarly, upon leavingsuch a predetermined area, either the server 400 or the client device300A may again initiate the grouping process to find another group 110for the client device 300A.

In yet other embodiments, the server 104 may initiate the groupingprocess for the client device 300A with the intent of removing theclient device 300A from its current group 110 in response to unwanted,objectionable, or fraudulent behavior by the user of the client device300A. For example, other member client devices 300B of the group 110 maysignal the server 104 to request that the client device 300A be removedfrom the group 110. Depending on the number and nature of the requestsfrom the other client devices 300B, the server 400 may either reinitiatethe grouping process while requiring the client device 300A to beremoved from the current group 110, or just unilaterally remove theclient device 300A from the group 110 without attempting to join theoffending client device 300A to another group 110. In anotherimplementation, the server 110 may perform such actions without requestsor other input from the other client devices 300B of the group 110 byway of some algorithm or heuristic. For example, the server 104 may basea decision to exclude the client device 300A from the group 110 upondetection of the client device 300A posting an inordinate amount ofcontent 120, or posting objectionable content 120, such as inappropriatecomments, photos, and the like.

In the event that the client device 300A loses contact with the server400 for periods of time, and thus is not able to provide the pollingmessage 608 with the location and environmental data in a timely manner,the coasting module 310 of the client device 300A can determine whether(or for how long) the client device 300A remains in the joined group110. In one example, the server 400 pushes a set of guidelines orinstructions employed by the coasting module 310 to determine under whatconditions the client device 300A has left its selected group 110. Forexample, various conditions, such as a lack of contact with the server400 for a predetermined minimum period of time, movement by the clientdevice 300A exceeding some minimum distance, and/or possibly some changein interaction between the client device 300A and another client device300B (such as a “friend”), may cause the coasting module 310 todetermine that the client device 300A is no longer part of its selectedgroup 110.

While joined with a group 110, the client device 300A may upload contentthat is captured or generated in the client device 300A to the server400 for distribution to other member client devices 300B of the group110. FIG. 8 provides a flow diagram of a method 800 for distributing orsharing the content 120. For example, in response to the user of theclient device 300A activating a camera button of the client device 300A,entering text into the client device 300A, or performing a similaraction, the client device 300A captures the associated content 120(operation 802).

The client device 300A may also process the content 120, such as providethumbnail versions of a photo, as well as other information relating tothe photo, to generate additional data to be included with the content120 (operation 804). The client device 300A may also attach to thecontent 120 the various location and environmental metadata provided viathe location services module 304 and the environment detection module306, as well as possibly the identity of the client device 300A(operation 806). Other information regarding the content 120, such asbrightness and contrast scores for an image, may also be attached asmetadata to the content 120. The client device 300A may then upload thecontent 120 and attendant metadata to the server 400 via the API module402 (operation 808).

Upon receipt of the content 120 and metadata, the server 400 may thenprocess the content 120 (operation 810). In some examples, the server400, via the face detection/recognition module 422 and the image qualitydetection module 424, may modify the content 120, such as crop stillimages to show better show faces, or eliminate portions of images, orentire images, that are of poor quality. Further, the server 400 may becapable of associating user names with faces appearing in images, andproviding those names as metadata to the receiving client devices 300B.That information may also be employed in some embodiments to associateother client devices 300B with the group 110. The server 400 may employother types of processing of the content 120 in other examples.

The server 400 also determines the group 110 that the client device 300Ais currently associated with (operation 812). In one implementation, ifthe client device 300A has maintained contact with the server 400 priorto the uploading of the content 120 and associated metadata (operation808), the API module 402 may determine that the current group 110 withwhich the client device 300A is joined is the intended destination group110. If, instead, the client device 300A had previously lost contactwith the server 400, the server API module 402 may cause the groupcandidate ranker module 410 to determine, via the metadata associatedwith the content 120, if the client device 300A belonged with anothergroup 110 at the time the content 120 was captured or generated. Oncethe group 110 determination has been made, the API module 402 may alsostore the content 120 and associated metadata as a child data structureof the group data structure 500 associated with the group 110.

Once the group 110 associated with the client device 300A is determined,the server 400 may then download the content 120 and metadata via thepush/subscribe module 416 to the client devices 300B with the group 110(operation 814). For example, each of the other client devices 300B maybe sent a message indicating that the content 120 from the client device300A is available for download via the Comet model mentioned earlier. Insome implementations, the other client devices 300B may downloadthumbnail sketches or other forms of the content 120 prior todownloading the full content 120, depending on the size of the content120, the bandwidth available in the connection between the server 400and the other client devices 300B, and other factors.

After downloading the content 120 and any related metadata, thereceiving client device 300B may present the content 120 to the user(operation 816) such as by way of a user interface of the client device300B. Also, the content 120 may be archived in the client device 300Bfor subsequent retrieval and presentation to the user, such as by way ofa content “diary,” described below.

Other than content 120, other types of information can be pushed to anyof the client devices 300 of a particular group 110. This informationmay include, for example, a notification that another client device 300has joined the group 110 to which the client device 300 receiving thenotification is joined, and that a new group 110 is available to theclient device 300 receiving the notification. In one implementation,these notifications, including a notification of new content 120, may beprovided via the user interface of the receiving client module 300, suchas via an “inbox” window or similar area of the user interface.

FIGS. 9A through 9L provide screen views of an example user interface ofa client device 300A under various circumstances as described above. Forexample, FIGS. 9A through 9E provide a series of user interface views inwhich a user initiates an application on a client device, such as a“smart” phone, and provides information to identify the client device300A from among a group of client devices 300 represented on the userinterface. The application provides the content-sharing functionalitydescribed in at least one of the above examples. More specifically, FIG.9A, provides a start-up screen when the application is initiated. Theuser interface of FIG. 9B presents an input field 902 for a first nameof the user of the client device 300A. FIG. 9C shows a subsequent screenin which the input field 902 has been populated. Once the input field902 is filled, the application prompts the user to provide a self-photo(as shown in FIG. 9D) so that the user may be represented by a photo“icon” on subsequent screens. The self-photo is displayed in FIG. 9E. Atthis point, the application is ready for the user to utilize in joininggroups and sharing content. In FIGS. 9F through 9L to follow, thecontent being shared are still photo images and annotations, althoughother types of content may be shared as well.

FIG. 9F provides a screen view of the user interface while photos arebeing captured and distributed among a group of client devices 300 of agroup 110. The photo strip 904 along the right side of the screen arethe most recent photos that are being received in real-time from thevarious members of the group 110, with the most recent photo beinghighlighted in a large display window 906. A “ribbon” 908 of photoicons, each representing a member of the current group 110, is alsopresented to the user. In some examples, such as the example of FIG. 9F,each of the photos of the ribbon 908 is adjusted to reflect a relativeconnection strength or affinity of the client device 300A relative tothe group 110, based on one or more factors associated with the image,such as, for example, physical location and environmental data of thedevice associated with the image. In FIG. 9F, the higher relevance ofthe leftmost photo (associated with the present client device 300A) isindicated by the brightness and color content of the image in comparisonto the remaining photos of the ribbon 908, which are essentially devoidof color, and are darkened. Other ways of distinguishing the connectionstrength or affinity of the client devices 300, such as sharpness orsize, may also be employed. A group field 910 displays the names ofmembers of the current group 110. One of the icons (the silhouettedimage) shows that neither a name nor a photo icon is associated withthat particular client device 300.

FIG. 9G provides multiple content “diaries” 912, wherein each diary 912contains multiple content items that were distributed to a particulargroup 110 of client devices 300. The top diary represents the mostrecent group 110 with which the current client device 300 is or wasassociated. Each diary 912 is marked with the number of content items,the type of content, the names for each client device 300 associatedwith the group 110, and how long ago the most recent image for thatgroup 110 was captured.

FIG. 9H provides a screen view in the event of a group 110 created bythe client device 300A, and that currently contains only the presentclient device 300A, as shown via a group member area 914. The contentarea 916 shown below the group member area 914 lists the content itemsthat have been posted for that group 110, which have all been capturedby the current client device 300A.

FIG. 9I provides a list of annotations 918 posted by various members ofa group 110 in a type of “inbox” format. The annotations 918 arearranged alphabetically according to the name of the client device 300posting the annotation, although other arrangements, such aschronologically, are also possible. The annotations 918 may include, forexample, comments to photos, “likes,” and star ratings. As presented inFIG. 9I, each annotation 918 provides the name of the poster of theannotation 918, the name of the client device 300 to whom the annotation918 is directed, how long ago the annotation 918 was posted, a photoicon representing the poster, and the annotation 918.

FIG. 9J provides a screen view of a list of content items 920 (in thiscase, photos), with each photo marked with a user icon 922 of the posterof the photo, along with the name of the poster and how long ago thephoto was captured.

FIG. 9K depicts a screen view of several content diaries 924, similar tothose shown in FIG. 9G.

FIG. 9L illustrates another screen view of photos being posted inreal-time to a current group 110, similar to the example of FIG. 9F. Theuser interface includes a photo strip 932 of the most recent photosbeing posted to the group 110, a large display window 926 of one of thephotos, a photo icon ribbon 928 displaying the four members of the group110 and their relative connection strength or affinity via the icons,and a group field 930 listing the members of the group 110.

Attached below are three appendixes, with each appendix providing anexample Java® class of a function described above. Appendix 1 provides adefinition of a SignalsScorer class that accepts a set of functions anddata values, applies the functions to the data, and produces an outputscore. The class may take a valueFunction to be applied to each of thevalues individually, an agingFunction to modify each of the values basedon their age, an arrayFunction to apply a modifying function to thevalues as a group, and a finalFunction to generate the overall score forthe values. The SignalsScorer class is used by both an exampleContactScorer class (Appendix 2) and an example GroupPhotoRanker class(Appendix 3), both of which are shown below.

In Appendix 2, the example ContactScorer class (employed in the affinitycalculator module 408 of FIG. 4) produces an affinity score for oneclient device in relation to another client device based on anaggregation of a number of interactions between the client devices, suchas “likes” and text replies posted between the client devices, thenumber of times one of the client devices was joined to the same groupas the other client device (automatically or explicitly), and otherfactors. The produced score is ultimately used to determine whichcontacts should be placed in an active content list for a client device.

Appendix 3 provides the example GroupPhotoRanker class, which calculatesa score representing a connection strength or affinity for a clientdevice in relation to a candidate group based on, for example, a group“pin” score (representing an amount or degree of “pinning,” as describedabove), a group “join” score, a group “self-create” score, a friendcontribution score, a friend presence score, a “loneliness” score (asdiscussed earlier), a Wi-Fi proximity score, and a space-time score. TheGroupPhotoRanker class may be employed in the group content rankermodule 410 of FIG. 4.

As a result of at least some of the embodiments discussed herein,sharing of content, such as still images, video clip, audio segments,and textual data, may be shared easily among a number of client devicesthat form their own “network” based on previous or current physicalproximity, previous contacts between the various devices, and/or otherfactors. Such groups may be formed “on-the-fly” without the users of theclient devices forming or configuring the group beforehand, withoutexplicit authorization of the client devices, and without providingpersonally identifiable information of the users.

Modules, Components, and Logic

Certain embodiments are described herein as including logic or a numberof components, modules, or mechanisms. Modules may constitute eithersoftware modules (e.g., code embodied on a machine-readable medium or ina transmission signal) or hardware modules. A hardware module is atangible unit capable of performing certain operations and may beconfigured or arranged in a certain manner. In example embodiments, oneor more computer systems (e.g., a standalone, client, or server computersystem) or one or more hardware modules of a computer system (e.g., aprocessor or a group of processors) may be configured by software (e.g.,an application or application portion) as a hardware module thatoperates to perform certain operations as described herein.

In various embodiments, a hardware module may be implementedmechanically or electronically. For example, a hardware module maycomprise dedicated circuitry or logic that is permanently configured(e.g., as a special-purpose processor, such as a field programmable gatearray (FPGA) or an application-specific integrated circuit (ASIC)) toperform certain operations. A hardware module may also compriseprogrammable logic or circuitry (e.g., as encompassed within ageneral-purpose processor or other programmable processor) that istemporarily configured by software to perform certain operations. Itwill be appreciated that the decision to implement a hardware modulemechanically, in dedicated and permanently configured circuitry, or intemporarily configured circuitry (e.g., configured by software) may bedriven by cost and time considerations.

Accordingly, the term “hardware module” should be understood toencompass a tangible entity, be that an entity that is physicallyconstructed, permanently configured (e.g., hardwired) or temporarilyconfigured (e.g., programmed) to operate in a certain manner and/or toperform certain operations described herein. Considering embodiments inwhich hardware modules are temporarily configured (e.g., programmed),each of the hardware modules need not be configured or instantiated atany one instance in time. For example, where the hardware modulescomprise a general-purpose processor configured using software, thegeneral-purpose processor may be configured as respective differenthardware modules at different times. Software may accordingly configurea processor, for example, to constitute a particular hardware module atone instance of time and to constitute a different hardware module at adifferent instance of time.

Hardware modules can provide information to, and receive informationfrom, other hardware modules. Accordingly, the described hardwaremodules may be regarded as being communicatively coupled. Where multiplesuch hardware modules exist contemporaneously, communications may beachieved through signal transmission (e.g., over appropriate circuitsand buses) that connect the hardware modules. In embodiments in whichmultiple hardware modules are configured or instantiated at differenttimes, communications between such hardware modules may be achieved, forexample, through the storage and retrieval of information in memorystructures to which the multiple hardware modules have access. Forexample, one hardware module may perform an operation and store theoutput of that operation in a memory device to which it iscommunicatively coupled. A further hardware module may then, at a latertime, access the memory device to retrieve and process the storedoutput. Hardware modules may also initiate communications with input oroutput devices, and can operate on a resource (e.g., a collection ofinformation).

The various operations of example methods described herein may beperformed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implemented modulesthat operate to perform one or more operations or functions. The modulesreferred to herein may, in some example embodiments, compriseprocessor-implemented modules.

Similarly, the methods described herein may be at least partiallyprocessor-implemented. For example, at least some of the operations of amethod may be performed by one or processors or processor-implementedmodules. The performance of certain of the operations may be distributedamong the one or more processors, not only residing within a singlemachine, but deployed across a number of machines. In some exampleembodiments, the processor or processors may be located in a singlelocation (e.g., within a home environment, an office environment, or asa server farm), while in other embodiments the processors may bedistributed across a number of locations.

The one or more processors may also operate to support performance ofthe relevant operations in a “cloud computing” environment or as a“software as a service” (SaaS). For example, at least some of theoperations may be performed by a group of computers (as examples ofmachines including processors), these operations being accessible via anetwork (e.g., the Internet) and via one or more appropriate interfaces(e.g., APIs).

Electronic Apparatus and System

Example embodiments may be implemented in digital electronic circuitry,or in computer hardware, firmware, or software, or in combinationsthereof. Example embodiments may be implemented using a computer programproduct (e.g., a computer program tangibly embodied in an informationcarrier in a machine-readable medium) for execution by, or to controlthe operation of, data processing apparatus (e.g., a programmableprocessor, a computer, or multiple computers).

A computer program can be written in any form of programming language,including compiled or interpreted languages, and it can be deployed inany form, including as a stand-alone program or as a module, subroutine,or other unit suitable for use in a computing environment. A computerprogram can be deployed to be executed on one computer or on multiplecomputers at one site or distributed across multiple sites andinterconnected by a communications network.

In example embodiments, operations may be performed by one or moreprogrammable processors executing a computer program to performfunctions by operating on input data and generating output. Methodoperations can also be performed by, and apparatus of exampleembodiments may be implemented as, special purpose logic circuitry(e.g., a field programmable gate array (FPGA) or an application-specificintegrated circuit (ASIC)).

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on their respectivecomputers and having a client-server relationship to each other. Inembodiments deploying a programmable computing system, it will beappreciated that both hardware and software architectures may beconsidered. Specifically, it will be appreciated that the choice ofwhether to implement certain functionality in permanently configuredhardware (e.g., an ASIC), in temporarily configured hardware (e.g., acombination of software and a programmable processor), or a combinationof permanently and temporarily configured hardware may be a designchoice. Below are set forth hardware (e.g., machine) and softwarearchitectures that may be deployed in various example embodiments.

Example Machine Architecture and Machine-Readable Medium

FIG. 10 is a block diagram of a machine in the example form of acomputer system 1000 within which instructions for causing the machineto perform any one or more of the methodologies discussed herein may beexecuted. In alternative embodiments, the machine operates as astandalone device or may be connected (e.g., networked) to othermachines. In a networked deployment, the machine may operate in thecapacity of a server or a client machine in a server-client networkenvironment, or as a peer machine in a peer-to-peer (or distributed)network environment. The machine may be a personal computer (PC), atablet PC, a set-top box (STB), a Personal Digital Assistant (PDA), acellular telephone, a web appliance, a network router, switch or bridge,or any machine capable of executing instructions (sequential orotherwise) that specify actions to be taken by that machine. Further,while only a single machine is illustrated, the term “machine” shallalso be taken to include any collection of machines that individually orjointly execute a set (or multiple sets) of instructions to perform anyone or more of the methodologies discussed herein.

The example computer system 1000 includes a processor 1002 (e.g., acentral processing unit (CPU), a graphics processing unit (GPU), orboth), a main memory 1004, and a static memory 1006, which communicatewith each other via a bus 1008. The computer system 1000 may furtherinclude a video display unit 1010 (e.g., a liquid crystal display (LCD)or a cathode ray tube (CRT)). The computer system 1000 also includes analphanumeric input device 1012 (e.g., a keyboard), a user interface (UI)navigation device 1014 (e.g., a mouse), a disk drive unit 1016, a signalgeneration device 1018 (e.g., a speaker), and a network interface device1020. The computer system 1000 may also include a environmental inputdevice 1026 that may provide a number of inputs describing theenvironment in which the computer system 1000 or another device exists,including, but not limited to, any of a Global Positioning Sensing (GPS)receiver, a temperature sensor, a light sensor, a still photo or videocamera, an audio sensor (e.g., a microphone), a velocity sensor, agyroscope, an accelerometer, and a compass.

Machine-Readable Medium

The disk drive unit 1016 includes a machine-readable medium 1022 onwhich is stored one or more sets of data structures and instructions1024 (e.g., software) embodying or utilized by any one or more of themethodologies or functions described herein. The instructions 1024 mayalso reside, completely or at least partially, within the main memory1004 and/or within the processor 1002 during execution thereof by thecomputer system 1000, the main memory 1004 and the processor 1002 alsoconstituting machine-readable media.

While the machine-readable medium 1022 is shown in an example embodimentto be a single medium, the term “machine-readable medium” may include asingle medium or multiple media (e.g., a centralized or distributeddatabase, and/or associated caches and servers) that store the one ormore instructions 1024 or data structures. The term “non-transitorymachine-readable medium” shall also be taken to include any tangiblemedium that is capable of storing, encoding, or carrying instructionsfor execution by the machine and that cause the machine to perform anyone or more of the methodologies of the present subject matter, or thatis capable of storing, encoding, or carrying data structures utilized byor associated with such instructions. The term “non-transitorymachine-readable medium” shall accordingly be taken to include, but notbe limited to, solid-state memories, and optical and magnetic media.Specific examples of non-transitory machine-readable media include, butare not limited to, non-volatile memory, including by way of example,semiconductor memory devices (e.g., Erasable Programmable Read-OnlyMemory (EPROM), Electrically Erasable Programmable Read-Only Memory(EEPROM), and flash memory devices), magnetic disks such as internalhard disks and removable disks, magneto-optical disks, and CD-ROM andDVD-ROM disks.

Transmission Medium

The instructions 1024 may further be transmitted or received over acomputer network 1050 using a transmission medium. The instructions 1024may be transmitted using the network interface device 1020 and any oneof a number of well-known transfer protocols (e.g., HTTP). Examples ofcommunication networks include a local area network (LAN), a wide areanetwork (WAN), the Internet, mobile telephone networks, Plain OldTelephone Service (POTS) networks, and wireless data networks (e.g.,WiFi and WiMAX networks). The term “transmission medium” shall be takento include any intangible medium that is capable of storing, encoding,or carrying instructions for execution by the machine, and includesdigital or analog communications signals or other intangible media tofacilitate communication of such software.

CONCLUSION

Thus, a method and system to share content among several communicationdevices have been described. Although the present subject matter hasbeen described with reference to specific example embodiments, it willbe evident that various modifications and changes may be made to theseembodiments without departing from the broader scope of the subjectmatter. For example, while the majority of the discussion above notesthe use of the embodiments with respect to general-purpose computersystems and applications, other software- or firmware-based systems,such as electronic products and systems employing embedded firmware, mayalso be developed in a similar manner to that discussed herein.Accordingly, the specification and drawings are to be regarded in anillustrative rather than a restrictive sense. The accompanying drawingsthat form a part hereof, show by way of illustration, and not oflimitation, specific embodiments in which the subject matter may bepracticed. The embodiments illustrated are described in sufficientdetail to enable those skilled in the art to practice the teachingsdisclosed herein. Other embodiments may be utilized and derivedtherefrom, such that structural and logical substitutions and changesmay be made without departing from the scope of this disclosure. ThisDetailed Description, therefore, is not to be taken in a limiting sense.

Such embodiments of the inventive subject matter may be referred toherein, individually and/or collectively, by the term “invention” merelyfor convenience and without intending to voluntarily limit the scope ofthis application to any single invention or inventive concept if morethan one is in fact disclosed. Thus, although specific embodiments havebeen illustrated and described herein, it should be appreciated that anyarrangement calculated to achieve the same purpose may be substitutedfor the specific embodiments shown. This disclosure is intended to coverany and all adaptations or variations of various embodiments.Combinations of the above embodiments, and other embodiments notspecifically described herein, will be apparent to those of skill in theart upon reviewing the above description.

All publications, patents, and patent documents referred to in thisdocument are incorporated by reference herein in their entirety, asthough individually incorporated by reference. In the event ofinconsistent usages between this document and those documents soincorporated by reference, the usage in the incorporated reference(s)should be considered supplementary to that of this document; forirreconcilable inconsistencies, the usage in this document controls.

In this document, the terms “a” or “an” are used, as is common in patentdocuments, to include one or more than one, independent of any otherinstances or usages of “at least one” or “one or more.” In thisdocument, the term “or” is used to refer to a nonexclusive or, such that“A or B” includes “A but not B,” “B but not A,” and “A and B,” unlessotherwise indicated.

APPENDIX 1 SIGNALS SCORER CLASS packagecom.colorlabscolorlabs.server.logic.scorer; import java.util.List;import com.colorlabs.common.util.ListUtil; /**  * Scorer for a set ofsignals, most likely homogeneous by kind, that can use the same age and * value functions, and that should have their aggregate scores combinedusing a single  * arrayFunction.  */ public class SignalsScorer {private final FloatFn valueFunction; private final FloatFn ageFunction;private final FloatArrayFn arrayFunction; private final FloatFnfinalFunction; SignalsScorer(FloatFn valueFunction, FloatFn ageFunction,FloatArrayFn arrayFunction, FloatFn finalFunction) { this.valueFunction= valueFunction; this.ageFunction = ageFunction; this.arrayFunction =arrayFunction; this.finalFunction = finalFunction; } public staticSignalsScorer of(FloatFn valueFunction, FloatFn ageFunction,FloatArrayFn arrayFunction) { return new SignalsScorer(valueFunction,ageFunction, arrayFunction, null); } public static SignalsScorerof(FloatFn valueFunction, FloatFn ageFunction, FloatArrayFnarrayFunction, FloatFn finalFunction) { return newSignalsScorer(valueFunction, ageFunction, arrayFunction, finalFunction);} public float score(List<Signal> signals) { if(ListUtil.isNullOrEmpty(signals)) return 0.0f; float[ ] subScores = newfloat[signals.size( )]; for (int i = 0; i < signals.size( ); i++) {Signal signal = signals.get(i); subScores[i] =valueFunction.apply(signal.getValue( )) *ageFunction.apply(signal.getAge( )); } float arrayOutput =arrayFunction.apply(subScores); return finalFunction == null ?arrayOutput : finalFunction.apply(arrayOutput); } }

APPENDIX 2 CONTACT SCORER CLASS packagecom.colorlabs.server.logic.elastic; import java.util.List; importcom.google.common.collect.ArrayListMultimap; importcom.google.common.collect.ImmutableMap; importcom.google.common.collect.Lists; import com.google.inject.Inject; importcom.colorlabs.common.util.Clock; importcom.colorlabs.server.logic.scorer.SignalsScorer; importcom.colorlabs.server.logic.scorer.ArrayFunctions; importcom.colorlabs.server.logic.scorer.Functions; importcom.colorlabs.server.logic.scorer.Scorer; importcom.colorlabs.server.logic.scorer.Signal; importcom.colorlabs.server.proto.Storage; importcom.colorlabs.server.proto.WireData; /**  * Contact scorer V2implementation with newer Signals code.  */ public class ContactScorerV2implements ContactScorer { private static final float ONE_YEAR_MILLIS =1000 * 60 * 60 * 24 * 365; private static final float ONE_WEEK_MILLIS =1000 * 60 * 60 * 24 * 7; private final Clock clock; @Inject publicContactScorerV2(Clock clock) { this.clock = clock; } @Override publicfloat score(Storage.Contact target, WireData.Score.Builder scoreBuilder){ ArrayListMultimap<Signal.Kind, Signal> signals =extractSignals(target); float score = computeScoreFromSignals(signals);return score; } // Broadly applicable scorer that decays with a one yearhalf life, summing repeat interactions // with the asymptotic growthfunction. private static final SignalsScorerLONG_DECAY_ASYMPTOTIC_SUM_SCORER =SignalsScorer.of(Functions.constantFunction(1.0f),Functions.exponentialDecayFunction(ONE_YEAR_MILLIS), ArrayFunctions.sum(), Functions.asymptoticGrowthFunction(1.0f)); private static finalSignalsScorer NO_DECAY_ASYMPTOTIC_SUM_SCORER =SignalsScorer.of(Functions.constantFunction(1.0f),Functions.constantFunction(1.0f), ArrayFunctions.sum( ),Functions.asymptoticGrowthFunction(1.0f)); private static finalSignalsScorer COUNT_ONCE_SCORER =SignalsScorer.of(Functions.constantFunction(1.0f),Functions.constantFunction(1.0f), ArrayFunctions.max( )); private staticfinal SignalsScorer COUNT_ONCE_LONG_DECAY_SCORER =SignalsScorer.of(Functions.constantFunction(1.0f),Functions.cliffRampFunction(0.0f, ONE_YEAR_MILLIS * 10f),ArrayFunctions.max( )); private floatcomputeScoreFromSignals(ArrayListMultimap<Signal.Kind, Signal> signals){ float likeScore =LONG_DECAY_ASYMPTOTIC_SUM_SCORER.score(signals.get(Signal.Kind.ELASTIC_SELF_LIKE_MEDIA)); float addTextReplyScore =LONG_DECAY_ASYMPTOTIC_SUM_SCORER.score(signals.get(Signal.Kind.ELASTIC_SELF_ADD_TEXT_REPLY)); float autoJoinScore =LONG_DECAY_ASYMPTOTIC_SUM_SCORER.score(signals.get(Signal.Kind.ELASTIC_SELF_AUTO_JOIN_GROUP)); float explicitJoinScore =LONG_DECAY_ASYMPTOTIC_SUM_SCORER.score(signals.get(Signal.Kind.ELASTIC_SELF_EXPLICIT_JOIN_GROUP)); float addTextScore =LONG_DECAY_ASYMPTOTIC_SUM_SCORER.score(signals.get(Signal.Kind.ELASTIC_SELF_ADD_TEXT_GROUP)); float addMediaScore =LONG_DECAY_ASYMPTOTIC_SUM_SCORER.score(signals.get(Signal.Kind.ELASTIC_SELF_ADD_MEDIA_GROUP)); float inviteSentScore =COUNT_ONCE_SCORER.score(signals.get(Signal.Kind.ELASTIC_SELF_INVITE_SENT)); float inviteAcceptScore =COUNT_ONCE_SCORER.score(signals.get(Signal.Kind.ELASTIC_SELF_INVITE_ACCEPT)); // We only want to take the most recent action of this type.Thus, use a decaying count once // scorer and the higher end score wins.float blockValue =COUNT_ONCE_LONG_DECAY_SCORER.score(signals.get(Signal.Kind.ELASTIC_(—)SELF_EXPLICIT_BLOCK_USER)); float unblockValue =COUNT_ONCE_LONG_DECAY_SCORER.score(signals.get(Signal.Kind.ELASTIC_(—)SELF_EXPLICIT_UNBLOCK_USER)); float blockUnblockScore = blockValue >unblockValue ? −1.0f : 0.0f; // Same for explicit more / less, exceptwe'll take multiple actions as an even stronger // signal, hence thelong decay asymptotic sum scorer float explicitMoreUserScore =LONG_DECAY_ASYMPTOTIC_SUM_SCORER.score(signals.get(Signal.Kind.ELASTIC_SELF_EXPLICIT_MORE_USER)); float explicitLessUserScore =LONG_DECAY_ASYMPTOTIC_SUM_SCORER.score(signals.get(Signal.Kind.ELASTIC_SELF_EXPLICIT_LESS_USER)); // TODO: Think about how some scorersimpact each other - i.e. block/unblock, // only the latest should win.float score = 0.0f + 0.5f * likeScore + 0.3f * addTextReplyScore +0.01f * autoJoinScore + 0.05f * explicitJoinScore + 0.1f * addTextScore// disabled in v1 + 0.1f * addMediaScore // disabled in v1 + 1.0f *explicitMoreUserScore + −1.0f * explicitLessUserScore + 0.1f *inviteSentScore // not impl yet + 0.5f * inviteAcceptScore // not implyet + 1.0f * blockUnblockScore; return score; } privateArrayListMultimap<Signal.Kind, Signal> extractSignals(Storage.Contacttarget) { List<Signal> signals = Lists.newArrayList( ); for(Storage.Interaction interaction : target.getInteractionList( )) {Signal.Kind kind = INTERACTION_TO_KIND.get(interaction.getType( )); if(kind != null) { long timeDelta = delta(clock.now( ),interaction.getTimestampClient( )); signals.add(Signal.of(kind, 1.0f,timeDelta)); } } ArrayListMultimap<Signal.Kind, Signal> signalMultimap =ArrayListMultimap.create( ); for (Signal signal : signals) {signalMultimap.put(signal.getKind( ), signal); } return signalMultimap;} private long delta(long timeA, long timeB) { return Math.abs(timeA −timeB); } private static final ImmutableMap<Storage.Interaction.Type,Signal.Kind> INTERACTION_TO_KIND =ImmutableMap.<Storage.Interaction.Type, Signal.Kind>builder( ).put(Storage.Interaction.Type.LIKE_MEDIA,Signal.Kind.ELASTIC_SELF_LIKE_MEDIA).put(Storage.Interaction.Type.ADD_TEXT_REPLY,Signal.Kind.ELASTIC_SELF_ADD_TEXT_REPLY).put(Storage.Interaction.Type.AUTO_JOIN_GROUP,Signal.Kind.ELASTIC_SELF_AUTO_JOIN_GROUP).put(Storage.Interaction.Type.EXPLICIT_JOIN_GROUP,Signal.Kind.ELASTIC_SELF_EXPLICIT_JOIN_GROUP).put(Storage.Interaction.Type.ADD_TEXT_GROUP,Signal.Kind.ELASTIC_SELF_ADD_TEXT_GROUP).put(Storage.Interaction.Type.ADD_MEDIA_GROUP,Signal.Kind.ELASTIC_SELF_ADD_MEDIA_GROUP).put(Storage.Interaction.Type.EXPLICIT_MORE_USER,Signal.Kind.ELASTIC_SELF_EXPLICIT_MORE_USER).put(Storage.Interaction.Type.EXPLICIT_LESS_USER,Signal.Kind.ELASTIC_SELF_EXPLICIT_LESS_USER).put(Storage.Interaction.Type.INVITE_SENT,Signal.Kind.ELASTIC_SELF_INVITE_SENT).put(Storage.Interaction.Type.INVITE_ACCEPT,Signal.Kind.ELASTIC_SELF_INVITE_ACCEPT).put(Storage.Interaction.Type.EXPLICIT_BLOCK_USER,Signal.Kind.ELASTIC_SELF_EXPLICIT_BLOCK_USER).put(Storage.Interaction.Type.EXPLICIT_UNBLOCK_USER,Signal.Kind.ELASTIC_SELF_EXPLICIT_UNBLOCK_USER) .build( ); }

1-20. (canceled)
 21. A method, comprising: recording logicalrelationship information describing logical relationships between afirst user and other users, the logical relationship informationassociated with a social networking service; receiving content from afirst user device of the first user, the content having been generatedby the first user device; receiving content from a second user device ofthe second user, the content having been generated by the second userdevice; based on a determination that the content from the first userdevice and the content from the second user device were received withina preset amount of time of each other, creating a first user group towhich to associate the first user and the second user; and determining,at a server using at least one processor, whether to remove the first orsecond user from the first user group or to combine the first user groupwith at least one other user group based on the logical relationshipinformation and the content.
 22. The method of claim 21, wherein thecontent from the first user and the content from the second user bothcontain metadata, and the determining is further based on the metadatafor the content from the first user and the metadata for the contentfrom the second user.
 23. The method of claim 22, wherein the metadataincludes information indicating the physical location of the first userdevice when the content was generated.
 24. The method of claim 22,wherein the metadata includes environmental information of the firstuser device when the content was generated.
 25. The method of claim 21,further comprising combining the content from the first user and thecontent from the second user into a single data structure fortransmission to a plurality of users in the first user group.
 26. Themethod of claim 21, wherein the logical relationship informationincludes proximity information regarding the first user device at thetime the content was generated and other user devices.
 27. The method ofclaim 21, wherein the logical relationship information includesinformation indicating the proximity of the first user device to apreset physical location, at the time the content was generated.
 28. Themethod of claim 21, further comprising recording communications betweenthe first user and other users and between the second user and otherusers and wherein the determining is further based on the metadata forthe content from the first user and the metadata for the content fromthe second user.
 29. A system comprising: at least one processor; datastorage comprising modules including instructions to be executed by theat least one processor, the modules comprising: an interaction recordingmodule configured to record logical relationship information describinglogical relationships between a first user and other users, the logicalrelationship information associated with a social networking service; aninterface module configured to receive content from a first user deviceof the first user, the content having been generated by the first userdevice, and receive content from a second user device of the seconduser, the content having been generated by the second user device; and agroup ranker module configured to, based on a determination that thecontent from the first user device and the content from the second userdevice were received within a preset amount of time of each other,create a first user group to which to associate the first user and thesecond user, and determine whether to remove the first or second userfrom the first user group or to combine the first user group with atleast one other user group based on the logical relationship informationand the content.
 30. The system of claim 29, wherein the content fromthe first user and the content from the second user both containmetadata, and wherein the determining is further based on the metadatafor the content from the first user and the metadata for the contentfrom the second user.
 31. The system of claim 30, wherein the metadataincludes information indicating the physical location of the first userdevice when the content was generated.
 32. The system of claim 30,wherein the metadata includes environmental information of the firstuser device when the content was generated.
 33. The system of claim 29,further comprising a push module configured to the content from thefirst user and the content from the second user into a single datastructure for transmission to a plurality of users in the first usergroup.
 34. The system of claim 29, wherein the logical relationshipinformation includes proximity information regarding the first userdevice at the time the content was generated and other user devices. 35.The system of claim 29, wherein the logical relationship informationincludes proximity information regarding the first user device at thetime the content was generated and a preset physical location.
 36. Thesystem of claim 29, further comprising an interaction recording moduleconfigured to record communications between the first user and otherothers and between the second user and other users, wherein thedetermining is further based on the metadata for the content from thefirst user and the metadata for the content from the second user.
 37. Anon-transitory computer-readable storage medium comprising instructionsthat, when executed by at least one processor of a machine, cause themachine to perform operations comprising: recording logical relationshipinformation describing logical relationships between a first user andother users, the logical relationship information associated with asocial networking service; receiving content from a first user device ofthe first user, the content having been generated by the first userdevice; receiving content from a second user device of the second user,the content having been generated by the second user device; based on adetermination that the content from the first user device and thecontent from the second user device were received within a preset amountof time of each other, creating a first user group to which to associatethe first user and the second user; and determining, at a server usingat least one processor, whether to remove the first or second user fromthe first user group or to combine the first user group with at leastone other user group based on the logical relationship information andthe content.
 38. The non-transitory computer-readable storage medium ofclaim 37, wherein the content from the first user and the content fromthe second user both contain metadata, and wherein the determining isfurther based on the metadata for the content from the first user andthe metadata for the content from the second user.
 39. Thenon-transitory computer-readable storage medium of claim 38, wherein themetadata includes information indicating the physical location of thefirst user device when the content was generated.
 40. The non-transitorycomputer-readable storage medium of claim 38, wherein the metadataincludes environmental information of the first user device when thecontent was generated.